5 ms·

Reasons robotics is hard

130 points by ddp26 14d ago

UltraSane 14d ago
The physical world is basically an infinite amount of global state that must be perceived indirectly through imperfect sensors and acted on using imperfect motors and manipulators.
logicallee 14d ago
people very soon as going to look back at all of us and just think "they didn't even have robots yet! how did they even eat?" Well, future readers, it isn't easy! We either go to the store and bring back groceries ourselves or pay a helper to do it. No robot in the loop there. Then when it comes time to cook something we either have to cut it up and otherwise prepare it and then cook it ourselves, or another human can do it, or we can buy fully prepared foods that don't require cooking. And then when we're done we have to put our own dishes away into a dishwasher. We can't just say a few words and have a robot do it for us!
- robotresearcher 14d ago
  > We either go to the store and bring back groceries ourselves or pay a helper to do it. Or order it from Amazon, in which case there was likely a robot in the pipeline. Robots are very widely deployed, but almost entirely invisibly to the customer yet. Roomba is the main exception.
- NichoPaolucci 14d ago
  Eat? You must be living under a rock. We've been evaporating our sustenance and storing it in the cloud for years. Perhaps nanobots will be able to carry the chemical makeup of a cheeseburger and rebuild a bite directly in our mouths, no cooking necessary!
  - Nition 14d ago
    Remember though, there is no food cloud really, just other people's fridges.
    - TeMPOraL 13d ago
      There is a business idea sitting right there.
- ModernMech 14d ago
  As if people of the future will be able to read. Maybe some future AI anthropologists will read it though.
GlenTheMachine 14d ago
Roboticist here. All of this, and he didn’t mention compliance or online adaptation to otherwise un-sensable dynamics. Or massively complex miniature mechanisms. Current generation tactile sensors cost a couple thousand $ PER FINGER, and have a real world MTBF of hours. The cost can be solved with economy of scale. The fragility is harder.
- UltraSane 14d ago
  I'm picturing humanoid robots having to operate in pairs so they can constantly fix each other.
  - lizagub 14d ago
    i like this
  - lukan 13d ago
    Also so they can watch each other, in case of the humans trying to shut them down.
    - aleph_minus_one 13d ago
      > Also so they can watch each other, in case of the humans trying to shut them down. That's why the human operator needs a gun. :-)
- Onavo 14d ago
  > Current generation tactile sensors cost a couple thousand $ PER FINGER, and have a real world MTBF of hours. The cost can be solved with economy of scale. The fragility is harder. Are we talking about experimental laboratory ones here? What happens when the Alibaba players start getting into the game? They have plenty of humanoid robots.
  - dyauspitr 14d ago
    How much more sensitive do you need to be compared to say a standard mobile capacitive screen and those are essentially dirt cheap at this point.
kooi 14d ago
Yes the problem is very hard. Mainly because high DOF generalization is very difficult. We have self driving cars because what are the control inputs? Pedal, brake, steering wheel. This already took many many years. Now for a humanoid robot: An action space that is metaphorically Hilbert. (Physically, yes, obviously) Also, IMO, LLM's can aid the development of robots, but do little beyond a planning, human control interface. Below that it's the domain of control and the solution will be the correct combination of classical, neural, and real time optimization based control. All the bad-ass biped robots that actually look natural? It's PID controls wrapped with control barrier functions constraining the QPs that are being solved in real time. But that's annoying to derive per-application. So we'll need neural methods which can be learned (while being constrained by a priori knowledge of dynamics). My hunch is that the Yann LeCunn type of jepa models will be how tasks can be learned.
- mr_toad 14d ago
  > So we'll need neural methods which can be learned Data is a problem. LLMs had the advantage of the whole internet to train on. Robots don’t have that corpus of information. And real time learning seems to be something that everyone in AI is studiously ignoring.
  - robotresearcher 14d ago
    The hope is that RL in simulation can fill the gap. Also there’s imitating humans, via a suitable mapping from the human sensor, control and configuration space to the robot’s. Some groups have gathered video and other data from humans doing tasks, for example with a VR headset.
- gugagore 14d ago
  > All the bad-ass biped robots that actually look natural? It's PID controls wrapped with control barrier functions constraining the QPs that are being solved in real time. That's not entirely true. Locomotion is well addressed by RL in sim. It's true that there is still a PD layer, and the RL policy produces setpoints for it.
- dyauspitr 14d ago
akurilin 14d ago
Couple of related reads/watches to this I found useful recently, with a similar conclusion: https://www.youtube.com/watch?v=FUUzmRH5Yi4 https://www.youtube.com/watch?v=FUUzmRH5Yi4 https://www.construction-physics.com/p/robot-dexterity-still-seems-hard https://www.construction-physics.com/p/robot-dexterity-still...
choonway 14d ago
I can say many things, but most people here will not believe me. I'd say just watch China do the 'impossible'. Then some self reflection should be in order.
Ozzie-D 14d ago
[flagged]
Animats 14d ago
A marker of progress will be when Amazon converts to automated picking. They've been trying hard for almost a decade now. They had an annual competition for years. They have a decent picking robot developed in house.[1] It's not being deployed in quantity yet. Nor does it have anything like a humanoid hand. Just a two-surface gripper. Amazon's production robots are mostly automatic guided vehicles, not manipulators. I'm impressed with how far legged locomotion has come. But as yet, nobody seems to be using legged robots for any commercial purpose beyond the demo level. Is Tesla still going to produce vast numbers of humanoid robots by the end of 2026? There's been a lot of progress on the hardware side. Motor technology from drones has produced much better robot motors. The sweet spot on gear reduction seems to have been found. (Too much reduction, and you can't back drive. Too little, and the motors have to be too big.) The volumes are now large enough to justify making robot-specific components. Robot arms are much better than a decade ago. So are robot legs. Control is better, too. It looks like a humanoid robot will cost about as much as a car. But they're still not quite good enough to be useful. We'll know they are real when an Amazon Prime truck drives up and a robot does the last 100 meters of the delivery. [1] https://www.youtube.com/watch?v=WStK9HNn8c8& https://www.youtube.com/watch?v=WStK9HNn8c8&
- skybrian 14d ago
  Yes, picking is one, and package delivery is another. I wonder how many people currently get package deliveries by robot? It might be a good metric to track?
- honr 14d ago
  That would only be a minor marker. A major marker would be whatever the Chinese equivalent(s) of Amazon are (Alibaba? etc.) going that route successfully. From academic / industrial conference presentations it appears Chinese services are banking on automation far more than an entity like Amazon does. That being said, I don't know what exact state the industrial automation technology is there and I can only extrapolate (or do websearch, which didn't lead to enough details; I only found things like https://www.youtube.com/watch?v=JnUGgc8R3ng https://www.youtube.com/watch?v=JnUGgc8R3ng). When something like https://www.allegrohand.com https://www.allegrohand.com is mass produced and used industrially, I bet the last mile (meter?) would change a bit, and full automation would be easier and less finicky.
andsoitis 14d ago
hairstylists are safe. and manicurists. and outcall masseurs. really anything that involves a bade near your body or where body contact is the point.
- the_sleaze_ 14d ago
  They've already got a kind of masseur. You put on a spandex outfit to reduce friction and lay under 2 arms apparently. > https://www.aescape.com/ https://www.aescape.com/
  - andsoitis 14d ago
    that's neither sexy nor sensual. pass.
- deleted 13d ago
  [deleted]
YuechenLi 14d ago
I mean, functional robotics isn't that hard, robotic vacuums have been in homes for a decade now, and industrial robotic arms. However, humanoid robots IS hard mainly because of the form factor constraints. You can't really get a lot of power out of servo motors and other actuator if it all has to be self-contained in a humanoid form instead of using hydraulics or pneumonic or even big stepper motors as for stationary industrial robots. The videos I've seen of humanoid robot applications are basically that it can do dishes and fold laundry, but I think if household chore robots ever come to market, they would probably not look humanoid at all and probably look like semi dishwashers/washing machines with wheels and a gripper arm.
- imtringued 14d ago
  Electric motors are absurdly power dense compared to human muscle. The form factor has been solved basically everyone is building humanoid robots and hoping a transformer with a big enough dataset is going to do the rest.
_carbyau_ 14d ago
People think robots in terms of humanoid or number-5 style robots. I think it'll be more capable appliances at first. Like a lawn mowing device that also spots weeds and can spray them. Next iteration has arms to rip weeds out of the garden. Next has attachments so you can direct it to do pruning. Next it can figure out the pruning itself and move the outcome into the woodchipper. And so on and so on. It's not going to be one day a humanoid robot comes into the house and does everything.
- horsawlarway 14d ago
  While I agree this is a technical path that makes sense, I'm not sure it's a financial path that does. Or at least not outside of very upscale, niche products for wealthy consumers or businesses. Which doesn't mean I disagree with you. I also think that this progression is the most likely. But it implies we're decades away from broad adoption rates. Think fifty years to hit mass adoption, not five. (Because that much more closely aligns with other structurally disruptive tech like automobiles or computers) Which is definitely not the story being pitched to investors at the moment.
  - _carbyau_ 13d ago
    > Or at least not outside of very upscale, niche products for wealthy consumers or businesses. Products that start life as "for the rich, first adopters" and work their way down the economic classes are a thing. Whether it is the thing in this case I don't know. > Which is definitely not the story being pitched to investors at the moment. I would think that what is pitched is what investors want to hear....
- gandalfgreybeer 14d ago
  Sometimes, I wonder why we even need humanoid robots for some tasks. For example, we had that robot over the past year that would wash the dishes...would be more efficient if it had 8 arms for that job. Or if I wanted it to clean my room, an arm that can extend up to the ceiling.
- Animats 13d ago
  > Like a lawn mowing device that also spots weeds and can spray them. That's available as a tractor-pulled implement for farms. Deere and some others make such things.
tintor 14d ago
“If a self-driving car finds itself in a situation it can’t handle or suffers a glitch, it can pull over or, in the worst case, just hit the brakes.” Wrong. Try hitting the brakes of your self driving car on highway at 65mph or during unprotected left turn with oncoming vehicles. Or have a glitched self-driving car hit its brakes and block the road, for emergency vehicles, and endangering other people. Self-driving cars can also suffer a glitch without knowing they suffered a glitch, like Waymo cars driving into flooded roads.
tintor 14d ago
“I may not care if my household robot takes all night to tidy up and fold the laundry.” I do. I don’t want robot vacuuming or making noise at night or doing something potentially dangerous unmonitored while people are asleep.
- xxs 13d ago
  Small cleaning robots have existed for long enough. For floor sweeping they are more efficient than any 2-legged form. Not folding the laundry, though.
  - bananaflag 13d ago
    Not for the kind of floor I have with tons of obstacles and small corners.
pinkmuffinere 13d ago
> I am confused at how Waymo engineering can be so robust as to yield an astonishingly good safety record, and yet so slapdash as to happily drive into deep water. I feel this is actually somewhat straightforward. I assume deep water on roadways is not commonly in the training set, because frankly it isn't common in real life, and when it is common people do not drive and do not gather that training data. As a result the proper response has not adequately been beaten into the models. There are probably also challenges of world-sensing, since water can act as a mirror, and maybe other complications. So waymos are bad at handling deep water on roadways. However, deep water on roadways is also not common in the areas where waymos are deployed. As a result, waymo's have a great safety record, and at the same time they make mistakes that are obvious to a human. A common criticism of AI discourse is that people act as if LLM's "think". I don't want to be a vocabulary purist, but I suspect that's related to the astonishment here -- the Waymo doesn't know what flooding is, it doesn't fear drowning, it doesn't think. So unless it's been repeatedly trained, or a special case has been hard coded by manual effort, it doesn't know that flooded roadways are dangerous. I have made a lot of assumptions here, and I don't truthfully know what the training data looks like. Feel free to push back if you think my assumptions are wrong. I'd especially be interested if somebody can show that water on roadways _is_ in the training data
- alex43578 13d ago
  People drive into deep water all the time - some states specifically have laws making them financially liable for the cost of rescue because it’s such a stupid thing to do. But still, they do it.
  - pinkmuffinere 13d ago
    I think the fact that there are laws about it is not good evidence that it should be in the training data. Laws often cover weird edge cases, and if an edge case happens 50 times in 100 years, there's likely a law covering it. At the same time, that's probably not enough occurrences for it to naturally end up in a dataset -- the edge case would probably need to be intentionally sought out. I'm not saying that driving-in-deep water only happens 50 times in 100 years, it's certainly more common than that, I'm just saying that despite laws on the topic, it may still be too rare to be well represented in training data. For example, in real life I've only seen a car drive into deep water once. Even if we include recordings that I've seen, that would maybe bring it up to 20?
AngryData 13d ago
This is why im not worried about "AI" taking over the world. Robotics still has a LONG way to go. A human can balance a plate on their arm with food while holding a glass of milk in that hand and a donut in the other and still manage to open a door, step over potential floor obstacles, maneuver tight spaces, get bumped by a child or dog, and still set it all down without spilling it 99% of the time. Just the hardware with the dexterity and responsiveness to perform the same task would cost unimaginable amounts of money to produce, not to mention the control systems needed to do it smooth and gracefully enough. Maybe in another 2 decades I could see it possibly starting to change, but even then I wouldn't bet the horse on it until I saw it. Cars only have three degrees of freedom and even that we are barely able to get working well enough to put it into limited practice. And yet one single human finger has atleast 3 degrees of freedom, and is covered in what is the equivalent of a million tiny ultra sensitive tactile sensors.
- philot 13d ago
  This is true, but it’s also assuming the robot has to be human shaped. A robot with 4 extendable arms and a gyroscopically balanced cabinet in its chest wouldn’t have too much trouble with that task.
  - AngryData 13d ago
    How many other tasks is it not suited for now though? If we wanted a device to automate limited specific tasks then we don't need advanced highly advanced robotics. A human has strength, dexterity, high balance, very sensitive tactile touch, can move both fast and slow, is very compact, etc. A robot has to have serious tradeoffs just to hit two of those things. A robot arm that is capable of threading a needle is likely not suited to chopping some wood or carrying groceries. And if you just add a bunch of different arms for different tasks it becomes way more complex, expensive, heavy, and inefficient.
shevy-java 13d ago
Another example of how AI dumbs down everything. > Once they have context, robots will need to reason, plan, and exercise judgement and common sense. LLM-based systems like ChatGPT and Claude are making great strides in these areas But why would I want to make AI more powerful - and disruptive - than it already is? I don't see this as a benefit but as a disadvantage. Let's also not forget that e. g. Google deliberately ruined its search engine. Now if you search something, by default, you get AI slop results that are often not truthful or only partially truthful. This is a private web. Google wants to control information.
techsage 13d ago
[dead]
andai 13d ago
Felt obligated to repeat this linked video here for posterity: https://youtube.com/watch?v=weXDUc5Osto https://youtube.com/watch?v=weXDUc5Osto
chrisjj 13d ago
> AI progress is racing along, but virtually all of the visible progress is in the realm of knowledge work, i.e. activities that can take place inside a computer. The most visible "progress" of so-called AI is in activities that take place at the interface between computers and gullible humans. The reason so much less progress has been made in robots is that real-world physics isn't gullible.
fatbird 13d ago
I've yet to see anyone address the more immediate problem for (humaniform) robotics, which is that it runs counter to the economic benefits of specialization at industrial scales. A robotic warehouse that's just like a human warehouse but with robots walking the aisles will always be more expensive (and likely far less efficient) than a warehouse purpose built for automated picking using standard containers and graspers, conveyer belts or path constrained wheeled platforms--something I've seen in operation 20 years ago. A factory of general purpose robots sewing t-shirts will always be more expensive than a factory a low wage humans sitting there doing the same. The Fourdrinier process for making flat-sheet goods (i.e., paper, thin plastic, in massive rolls) is more than two centuries old. The idea that robots, returning to dipping a mould into the furnish to create individual sheets, could even come close to the economics of modern papermaking is insane. [0] https://en.wikipedia.org/wiki/Paper_machine https://en.wikipedia.org/wiki/Paper_machine
b89kim 12d ago
Main problem of humnoid is price. Price starts from 20,000$ and we need jetson thor(On-device) or 5090 for learning capabilities. Their ability per cost is not greater than human. The other problem is hard to predict/simulate real world contact physics. Thus, most of company use VLA for task with contact. Even if VLA is advancing rapidly, it's still immature to be deployed in practical.

130 points by ddp26 14d ago

The physical world is basically an infinite amount of global state that must be perceived indirectly through imperfect sensors and acted on using imperfect motors and manipulators.

logicallee 14d ago

people very soon as going to look back at all of us and just think "they didn't even have robots yet! how did they even eat?" Well, future readers, it isn't easy! We either go to the store and bring back groceries ourselves or pay a helper to do it. No robot in the loop there. Then when it comes time to cook something we either have to cut it up and otherwise prepare it and then cook it ourselves, or another human can do it, or we can buy fully prepared foods that don't require cooking. And then when we're done we have to put our own dishes away into a dishwasher. We can't just say a few words and have a robot do it for us!

robotresearcher 14d ago
> We either go to the store and bring back groceries ourselves or pay a helper to do it. Or order it from Amazon, in which case there was likely a robot in the pipeline. Robots are very widely deployed, but almost entirely invisibly to the customer yet. Roomba is the main exception.
NichoPaolucci 14d ago
Eat? You must be living under a rock. We've been evaporating our sustenance and storing it in the cloud for years. Perhaps nanobots will be able to carry the chemical makeup of a cheeseburger and rebuild a bite directly in our mouths, no cooking necessary!
- Nition 14d ago
  Remember though, there is no food cloud really, just other people's fridges.
  - TeMPOraL 13d ago
    There is a business idea sitting right there.
ModernMech 14d ago
As if people of the future will be able to read. Maybe some future AI anthropologists will read it though.

GlenTheMachine 14d ago

Roboticist here. All of this, and he didn’t mention compliance or online adaptation to otherwise un-sensable dynamics. Or massively complex miniature mechanisms. Current generation tactile sensors cost a couple thousand $ PER FINGER, and have a real world MTBF of hours. The cost can be solved with economy of scale. The fragility is harder.

UltraSane 14d ago
I'm picturing humanoid robots having to operate in pairs so they can constantly fix each other.
- lizagub 14d ago
  i like this
- lukan 13d ago
  Also so they can watch each other, in case of the humans trying to shut them down.
  - aleph_minus_one 13d ago
    > Also so they can watch each other, in case of the humans trying to shut them down. That's why the human operator needs a gun. :-)
Onavo 14d ago
> Current generation tactile sensors cost a couple thousand $ PER FINGER, and have a real world MTBF of hours. The cost can be solved with economy of scale. The fragility is harder. Are we talking about experimental laboratory ones here? What happens when the Alibaba players start getting into the game? They have plenty of humanoid robots.
- dyauspitr 14d ago
  How much more sensitive do you need to be compared to say a standard mobile capacitive screen and those are essentially dirt cheap at this point.

kooi 14d ago

Yes the problem is very hard. Mainly because high DOF generalization is very difficult. We have self driving cars because what are the control inputs? Pedal, brake, steering wheel. This already took many many years. Now for a humanoid robot: An action space that is metaphorically Hilbert. (Physically, yes, obviously) Also, IMO, LLM's can aid the development of robots, but do little beyond a planning, human control interface. Below that it's the domain of control and the solution will be the correct combination of classical, neural, and real time optimization based control. All the bad-ass biped robots that actually look natural? It's PID controls wrapped with control barrier functions constraining the QPs that are being solved in real time. But that's annoying to derive per-application. So we'll need neural methods which can be learned (while being constrained by a priori knowledge of dynamics). My hunch is that the Yann LeCunn type of jepa models will be how tasks can be learned.

mr_toad 14d ago
> So we'll need neural methods which can be learned Data is a problem. LLMs had the advantage of the whole internet to train on. Robots don’t have that corpus of information. And real time learning seems to be something that everyone in AI is studiously ignoring.
- robotresearcher 14d ago
  The hope is that RL in simulation can fill the gap. Also there’s imitating humans, via a suitable mapping from the human sensor, control and configuration space to the robot’s. Some groups have gathered video and other data from humans doing tasks, for example with a VR headset.
gugagore 14d ago
> All the bad-ass biped robots that actually look natural? It's PID controls wrapped with control barrier functions constraining the QPs that are being solved in real time. That's not entirely true. Locomotion is well addressed by RL in sim. It's true that there is still a PD layer, and the RL policy produces setpoints for it.
dyauspitr 14d ago

akurilin 14d ago

Couple of related reads/watches to this I found useful recently, with a similar conclusion: https://www.youtube.com/watch?v=FUUzmRH5Yi4 https://www.youtube.com/watch?v=FUUzmRH5Yi4 https://www.construction-physics.com/p/robot-dexterity-still-seems-hard https://www.construction-physics.com/p/robot-dexterity-still...

choonway 14d ago

I can say many things, but most people here will not believe me. I'd say just watch China do the 'impossible'. Then some self reflection should be in order.

Ozzie-D 14d ago

[flagged]

Animats 14d ago

A marker of progress will be when Amazon converts to automated picking. They've been trying hard for almost a decade now. They had an annual competition for years. They have a decent picking robot developed in house.[1] It's not being deployed in quantity yet. Nor does it have anything like a humanoid hand. Just a two-surface gripper. Amazon's production robots are mostly automatic guided vehicles, not manipulators. I'm impressed with how far legged locomotion has come. But as yet, nobody seems to be using legged robots for any commercial purpose beyond the demo level. Is Tesla still going to produce vast numbers of humanoid robots by the end of 2026? There's been a lot of progress on the hardware side. Motor technology from drones has produced much better robot motors. The sweet spot on gear reduction seems to have been found. (Too much reduction, and you can't back drive. Too little, and the motors have to be too big.) The volumes are now large enough to justify making robot-specific components. Robot arms are much better than a decade ago. So are robot legs. Control is better, too. It looks like a humanoid robot will cost about as much as a car. But they're still not quite good enough to be useful. We'll know they are real when an Amazon Prime truck drives up and a robot does the last 100 meters of the delivery. [1] https://www.youtube.com/watch?v=WStK9HNn8c8& https://www.youtube.com/watch?v=WStK9HNn8c8&

skybrian 14d ago
Yes, picking is one, and package delivery is another. I wonder how many people currently get package deliveries by robot? It might be a good metric to track?
honr 14d ago
That would only be a minor marker. A major marker would be whatever the Chinese equivalent(s) of Amazon are (Alibaba? etc.) going that route successfully. From academic / industrial conference presentations it appears Chinese services are banking on automation far more than an entity like Amazon does. That being said, I don't know what exact state the industrial automation technology is there and I can only extrapolate (or do websearch, which didn't lead to enough details; I only found things like https://www.youtube.com/watch?v=JnUGgc8R3ng https://www.youtube.com/watch?v=JnUGgc8R3ng). When something like https://www.allegrohand.com https://www.allegrohand.com is mass produced and used industrially, I bet the last mile (meter?) would change a bit, and full automation would be easier and less finicky.

andsoitis 14d ago

hairstylists are safe. and manicurists. and outcall masseurs. really anything that involves a bade near your body or where body contact is the point.

the_sleaze_ 14d ago
They've already got a kind of masseur. You put on a spandex outfit to reduce friction and lay under 2 arms apparently. > https://www.aescape.com/ https://www.aescape.com/
- andsoitis 14d ago
  that's neither sexy nor sensual. pass.
deleted 13d ago
[deleted]

YuechenLi 14d ago

I mean, functional robotics isn't that hard, robotic vacuums have been in homes for a decade now, and industrial robotic arms. However, humanoid robots IS hard mainly because of the form factor constraints. You can't really get a lot of power out of servo motors and other actuator if it all has to be self-contained in a humanoid form instead of using hydraulics or pneumonic or even big stepper motors as for stationary industrial robots. The videos I've seen of humanoid robot applications are basically that it can do dishes and fold laundry, but I think if household chore robots ever come to market, they would probably not look humanoid at all and probably look like semi dishwashers/washing machines with wheels and a gripper arm.

imtringued 14d ago
Electric motors are absurdly power dense compared to human muscle. The form factor has been solved basically everyone is building humanoid robots and hoping a transformer with a big enough dataset is going to do the rest.

_carbyau_ 14d ago

People think robots in terms of humanoid or number-5 style robots. I think it'll be more capable appliances at first. Like a lawn mowing device that also spots weeds and can spray them. Next iteration has arms to rip weeds out of the garden. Next has attachments so you can direct it to do pruning. Next it can figure out the pruning itself and move the outcome into the woodchipper. And so on and so on. It's not going to be one day a humanoid robot comes into the house and does everything.

horsawlarway 14d ago
While I agree this is a technical path that makes sense, I'm not sure it's a financial path that does. Or at least not outside of very upscale, niche products for wealthy consumers or businesses. Which doesn't mean I disagree with you. I also think that this progression is the most likely. But it implies we're decades away from broad adoption rates. Think fifty years to hit mass adoption, not five. (Because that much more closely aligns with other structurally disruptive tech like automobiles or computers) Which is definitely not the story being pitched to investors at the moment.
- _carbyau_ 13d ago
  > Or at least not outside of very upscale, niche products for wealthy consumers or businesses. Products that start life as "for the rich, first adopters" and work their way down the economic classes are a thing. Whether it is the thing in this case I don't know. > Which is definitely not the story being pitched to investors at the moment. I would think that what is pitched is what investors want to hear....
gandalfgreybeer 14d ago
Sometimes, I wonder why we even need humanoid robots for some tasks. For example, we had that robot over the past year that would wash the dishes...would be more efficient if it had 8 arms for that job. Or if I wanted it to clean my room, an arm that can extend up to the ceiling.
Animats 13d ago
> Like a lawn mowing device that also spots weeds and can spray them. That's available as a tractor-pulled implement for farms. Deere and some others make such things.

tintor 14d ago

“If a self-driving car finds itself in a situation it can’t handle or suffers a glitch, it can pull over or, in the worst case, just hit the brakes.” Wrong. Try hitting the brakes of your self driving car on highway at 65mph or during unprotected left turn with oncoming vehicles. Or have a glitched self-driving car hit its brakes and block the road, for emergency vehicles, and endangering other people. Self-driving cars can also suffer a glitch without knowing they suffered a glitch, like Waymo cars driving into flooded roads.

tintor 14d ago

“I may not care if my household robot takes all night to tidy up and fold the laundry.” I do. I don’t want robot vacuuming or making noise at night or doing something potentially dangerous unmonitored while people are asleep.

xxs 13d ago
Small cleaning robots have existed for long enough. For floor sweeping they are more efficient than any 2-legged form. Not folding the laundry, though.
- bananaflag 13d ago
  Not for the kind of floor I have with tons of obstacles and small corners.

pinkmuffinere 13d ago

> I am confused at how Waymo engineering can be so robust as to yield an astonishingly good safety record, and yet so slapdash as to happily drive into deep water. I feel this is actually somewhat straightforward. I assume deep water on roadways is not commonly in the training set, because frankly it isn't common in real life, and when it is common people do not drive and do not gather that training data. As a result the proper response has not adequately been beaten into the models. There are probably also challenges of world-sensing, since water can act as a mirror, and maybe other complications. So waymos are bad at handling deep water on roadways. However, deep water on roadways is also not common in the areas where waymos are deployed. As a result, waymo's have a great safety record, and at the same time they make mistakes that are obvious to a human. A common criticism of AI discourse is that people act as if LLM's "think". I don't want to be a vocabulary purist, but I suspect that's related to the astonishment here -- the Waymo doesn't know what flooding is, it doesn't fear drowning, it doesn't think. So unless it's been repeatedly trained, or a special case has been hard coded by manual effort, it doesn't know that flooded roadways are dangerous. I have made a lot of assumptions here, and I don't truthfully know what the training data looks like. Feel free to push back if you think my assumptions are wrong. I'd especially be interested if somebody can show that water on roadways _is_ in the training data

alex43578 13d ago
People drive into deep water all the time - some states specifically have laws making them financially liable for the cost of rescue because it’s such a stupid thing to do. But still, they do it.
- pinkmuffinere 13d ago
  I think the fact that there are laws about it is not good evidence that it should be in the training data. Laws often cover weird edge cases, and if an edge case happens 50 times in 100 years, there's likely a law covering it. At the same time, that's probably not enough occurrences for it to naturally end up in a dataset -- the edge case would probably need to be intentionally sought out. I'm not saying that driving-in-deep water only happens 50 times in 100 years, it's certainly more common than that, I'm just saying that despite laws on the topic, it may still be too rare to be well represented in training data. For example, in real life I've only seen a car drive into deep water once. Even if we include recordings that I've seen, that would maybe bring it up to 20?

AngryData 13d ago

This is why im not worried about "AI" taking over the world. Robotics still has a LONG way to go. A human can balance a plate on their arm with food while holding a glass of milk in that hand and a donut in the other and still manage to open a door, step over potential floor obstacles, maneuver tight spaces, get bumped by a child or dog, and still set it all down without spilling it 99% of the time. Just the hardware with the dexterity and responsiveness to perform the same task would cost unimaginable amounts of money to produce, not to mention the control systems needed to do it smooth and gracefully enough. Maybe in another 2 decades I could see it possibly starting to change, but even then I wouldn't bet the horse on it until I saw it. Cars only have three degrees of freedom and even that we are barely able to get working well enough to put it into limited practice. And yet one single human finger has atleast 3 degrees of freedom, and is covered in what is the equivalent of a million tiny ultra sensitive tactile sensors.

philot 13d ago
This is true, but it’s also assuming the robot has to be human shaped. A robot with 4 extendable arms and a gyroscopically balanced cabinet in its chest wouldn’t have too much trouble with that task.
- AngryData 13d ago
  How many other tasks is it not suited for now though? If we wanted a device to automate limited specific tasks then we don't need advanced highly advanced robotics. A human has strength, dexterity, high balance, very sensitive tactile touch, can move both fast and slow, is very compact, etc. A robot has to have serious tradeoffs just to hit two of those things. A robot arm that is capable of threading a needle is likely not suited to chopping some wood or carrying groceries. And if you just add a bunch of different arms for different tasks it becomes way more complex, expensive, heavy, and inefficient.

shevy-java 13d ago

Another example of how AI dumbs down everything. > Once they have context, robots will need to reason, plan, and exercise judgement and common sense. LLM-based systems like ChatGPT and Claude are making great strides in these areas But why would I want to make AI more powerful - and disruptive - than it already is? I don't see this as a benefit but as a disadvantage. Let's also not forget that e. g. Google deliberately ruined its search engine. Now if you search something, by default, you get AI slop results that are often not truthful or only partially truthful. This is a private web. Google wants to control information.

techsage 13d ago

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andai 13d ago

Felt obligated to repeat this linked video here for posterity: https://youtube.com/watch?v=weXDUc5Osto https://youtube.com/watch?v=weXDUc5Osto

chrisjj 13d ago

> AI progress is racing along, but virtually all of the visible progress is in the realm of knowledge work, i.e. activities that can take place inside a computer. The most visible "progress" of so-called AI is in activities that take place at the interface between computers and gullible humans. The reason so much less progress has been made in robots is that real-world physics isn't gullible.

fatbird 13d ago

I've yet to see anyone address the more immediate problem for (humaniform) robotics, which is that it runs counter to the economic benefits of specialization at industrial scales. A robotic warehouse that's just like a human warehouse but with robots walking the aisles will always be more expensive (and likely far less efficient) than a warehouse purpose built for automated picking using standard containers and graspers, conveyer belts or path constrained wheeled platforms--something I've seen in operation 20 years ago. A factory of general purpose robots sewing t-shirts will always be more expensive than a factory a low wage humans sitting there doing the same. The Fourdrinier process for making flat-sheet goods (i.e., paper, thin plastic, in massive rolls) is more than two centuries old. The idea that robots, returning to dipping a mould into the furnish to create individual sheets, could even come close to the economics of modern papermaking is insane. [0] https://en.wikipedia.org/wiki/Paper_machine https://en.wikipedia.org/wiki/Paper_machine

b89kim 12d ago

Main problem of humnoid is price. Price starts from 20,000$ and we need jetson thor(On-device) or 5090 for learning capabilities. Their ability per cost is not greater than human. The other problem is hard to predict/simulate real world contact physics. Thus, most of company use VLA for task with contact. Even if VLA is advancing rapidly, it's still immature to be deployed in practical.